Samsung Electronics Co., Ltd.

Jihee Kim

Simon J Gibbs

Abhijit Z Bendale

Lu Luo

Anthony S Liot

Pranav K Mistry

Sajid Hassan Sadi

Joonghee Kim

Jungheun Hwang

Zhihan Ying

Bo Li

Hyun Jae Kang

Hyun-Chul Yoon

Kushal Kardam Vyas

Won J Jeon

Hanna Fuhrmann

Hyunchul Yoon

Yeongshin Park

Stanislaw Antol

Sung Ho Park

Sergio Perdices-Gonzalez

Dongjun Shin

Brian Thomas Harms

Cathy Kim

Link Chun Huang

Kathleen Sofia Hajash

Ye Zhao

Anil Unnikrishnan

Thomas Brenner

Kukhan Yoon

Taeseop Choi

Imran Mohammed

Ruokan He

Megan Rowe

Michael Noh

Jason Yeh

Hanseung Kwak

Yeong-Shin Park

Sungun Kwon

Sunghoon Choi

Abhijit Balaji

Yingying Ren

Mincheol Kwak

Arnaud Renevier

Sergi Perdices-Gonzalez

Samara Ren

Brian Harms

Saji Sadi

In one embodiment, a method includes accessing an initial image and applying each image filter from a set of one or more N image filters to the initial image to create N filtered images. The method further includes generating a similarity metric for each pair of images in a set of images comprising the initial image and the N filtered images and determining, based on the similarity metrics, a placement of each image in the set of images within an image-filter space. The method further includes generating, based on the image-filter space, a selectable image-filter interface; and providing the selectable image-filter interface for display, wherein each selectable region of the selectable image-filter interface is associated with a particular filtering of the initial image.

Image-filtering interface

In one embodiment, a method includes accessing an input image associated with an initial illumination, extracting from the input image at least a first, a second, and a third mono-channel images based on a first, a second, a third image channel, respectively, determining a first, a second, and a third correction for the first, second, and third mono-channel images with a first, a second, and a third correction algorithm, respectively, generating a first, a second, and a third corrected mono-channel image by applying the first, second, and third correction to the first, second, and third mono-channel image, respectively, and generating an output corrected image corresponding to the input image based on the first, second, and third mono-channel corrected images, wherein the output corrected image is associated with a corrected illumination with respect to the initial illumination.

Systems and methods for lightweight machine learning for image illumination control

Disclosed are semiconductor devices and their fabrication methods. The method includes forming an etching target on a substrate including cell and key regions, forming lower and upper mask layers on the etching target, performing photolithography to form an upper mask pattern including a hole on the cell region, a preliminary key pattern on the key region, a bar pattern on the key region, and a trench between the preliminary key pattern and the bar pattern, forming pillar and dam patterns filling the hole and the trench, performing photolithography to remove the upper mask pattern except for the bar pattern, using the pillar pattern, the dam pattern, and the bar pattern as an etching mask to form a lower mask pattern, and using the lower mask pattern as an etching mask to form an etching target pattern on the cell region and a key pattern on the key region.

Method of fabricating semiconductor device using multipe photolithography for patterning

A semiconductor device includes bit line structures disposed on a substrate, each bit line structure comprising a bit line and an insulating spacer structure, buried contacts which fill lower portions of spaces between bit line structures in the substrate, and landing pads which fill upper portions of the spaces, extend from upper surfaces of the buried contacts to upper surfaces of the bit line structures, and are spaced apart from each other by insulating structures. A first insulating structure is disposed between a first landing pad and a first bit line structure. The first insulating structure includes a sidewall extending along a sidewall of the first landing pad toward the substrate. In a direction extending toward the substrate, the sidewall of the first insulating structure gets closer to a first sidewall of the first bit line structure.

Semiconductor devices having air spacer

In order to manufacture an integrated circuit device, a feature layer is formed on a substrate in a first area for forming a plurality of chips and in a second area surrounding the first area. The feature layer has a step difference in the second area. On the feature layer, a hard mask structure including a plurality of hard mask layers stacked on each other is formed. In the first area and the second area, a protective layer covering the hard mask structure is formed. On the protective layer, a photoresist layer is formed. A photoresist pattern is formed by exposing and developing the photoresist layer in the first area by using the step difference in the second area as an alignment key.

Method of manufacturing integrated circuit device

A computer-implemented method of providing an emotion-aware reactive interface in an electronic device includes receiving an image of a user as an input and identifying a multi-modal non-verbal cue in the image. The method further includes interpreting the multi-modal non-verbal cue to determine a categorization and outputting a reactive interface event determined based on the categorization.

Emotion-aw are reactive interface

A device may include a camera configured to capture a live image data comprising an image of an object, and a processor coupled to the camera. The processor may be configured to recognize content of a selected portion of the live image data based on a contextual information relevant to the object using computer vision technology, and generate a visual information based on the recognized content. The device may also include an interface circuitry coupled to the processor. The interface circuitry may be configured to present the live image data, and overlay the live image data with the visual information.

Augmented reality device and operation thereof

A method includes retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof. At least one model is identified from multiple models based on the contextual information and at least one object recognized in an image based on at least one model. At least one icon is displayed at the device. The at least one icon being associated with at least one of an application, a service, or a combination thereof providing additional information.

System and method for contextual driven intelligence

One embodiment provides a method comprising classifying one or more objects present in an input comprising visual data by executing a first set of models associated with a domain on the input. Each model corresponds to an object category. Each model is trained to generate a visual classifier result relating to a corresponding object category in the input with an associated confidence value indicative of accuracy of the visual classifier result. The method further comprises aggregating a first set of visual classifier results based on confidence value associated with each visual classifier result of each model of the first set of models. At least one other model is selectable for execution on the input based on the aggregated first set of visual classifier results for additional classification of the objects. One or more visual classifier results are returned to an application running on an electronic device for display.

Vision intelligence management for electronic devices

In one embodiment, a computing system may access one or more frames of media content with each frame corresponding to at least part of an image. The computing system may automatically detect at least one object in at least one of the one or more frames. The computing system may automatically identify the at least one object. For each of the identified objects, the computing system may automatically determine an annotation corresponding to that object and each annotation may include one or more graphical elements. For each annotation, the computing system may automatically associate that annotation for display with its corresponding object.

Augmented reality

Disclosed is a method of fabricating a semiconductor device. The method comprises stacking an etching target layer, a first mask layer, an under layer, and a photoresist layer on a substrate, irradiating extreme ultraviolet (EUV) radiation on the photoresist layer to form a photoresist pattern, and performing a nitrogen plasma treatment on the photoresist pattern while using the first mask layer as an etching stop layer, the performing continuing until a top surface of the first mask layer is exposed. During the performing, the under layer is etched to form an under pattern below the photoresist pattern.

Method of manufacturing semiconductor device

Growing community of inventors

Mountain View, CA, United States of America

Jihee Kim